80% Faster Bank Reconciliation Through RPA-Driven Automation
The project was designed to automate the complete bank reconciliation process by eliminating the manual effort involved in matching bank transactions with Oracle ERP financial records. Using RPA and rule-based automation, MT940 bank statements are automatically read, transaction types are identified and classified, and bank entries are matched with corresponding ERP records. Reconciled entries are then automatically created in Oracle ERP, resulting in significantly faster reconciliation cycles, improved data accuracy, and more timely and reliable financial reporting.
Client Overview
The client is a leading enterprise operating across multiple business segments with high volumes of bank transactions. The finance team performs daily and monthly bank reconciliations for multiple bank accounts. It requires an automated solution to reduce processing time, minimize errors, and ensure accurate and timely financial data.
Technical Stack
Industry
Investment Management
Region
UAE (Sultanate-wide implementation)
Project-size
Non-Disclosable
Company size
Large Scale Authority (National Government Body)
Implementation Highlights
Automated MT940 statement processing: Enabled automated ingestion and reading of MT940 bank statements from multiple banks, ensuring consistent interpretation and accurate extraction of transaction data.
Rule-based transaction categorisation: Implemented a business-rules engine to intelligently classify transactions such as payments, receipts, cheques, SWIFT transfers, POS settlements, and bank charges.
ERP-driven transaction matching: Matched bank transactions with Oracle ERP records using reference numbers, amount matching, pattern recognition, and date tolerance to maximise auto-match accuracy.
Automated ERP reconciliation posting:
Automatically generated reconciled journal entries in Oracle ERP, eliminating manual posting effort and ensuring timely and accurate financial reporting.
Challenges & Solutions
Handling Complex and Inconsistent MT940 File Structures Across Multiple Banks
Solution: A robust MT940 parser was developed to recognise all MT940 tag types and variations. Fallback logic and rule-based identification were built in to handle exceptions and incomplete data, ensuring every file could be interpreted accurately regardless of the originating bank.
Managing Multiple Transaction Categories and Business Exceptions During Reconciliation
Solution: A configurable rules engine was built within the RPA platform to intelligently classify transactions based on business logic. This allowed the bot to automatically identify and categorise each transaction type, manage exceptions, and ensure consistent handling across all bank accounts.
Scaling Reconciliation to Handle Very High Daily Transaction Volumes Efficiently
Solution: The automation framework was designed to be fully scalable, enabling thousands of transactions to be processed within minutes. This ensured timely daily reconciliations while significantly reducing manual workload and operational pressure.
Achieving Accurate Matching with Oracle ERP Despite Limited and Inconsistent Reference Data
Solution: Advanced SQL-based pattern search logic was implemented to compare multiple matching parameters, including amount, reference fields, vendor names, cheque numbers, and date tolerances. This significantly increased auto-match rates, even when complete references were not available.
Identifying and Managing Non-Matchable Transactions Requiring Manual Finance Review
Solution: Unmatched transactions were automatically extracted into a structured Excel report, clearly highlighted for finance teams to review and resolve manually. This improved transparency, reduced investigation time, and ensured no transaction was overlooked.
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Agile enabled
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Results & Impact
- Achieved up to 80% faster bank reconciliation cycles — reducing processing time from hours to just minutes per day.
- Significantly reduced month-end closing time by automating high-volume reconciliation activities across multiple bank accounts.
- Delivered 100% accuracy for all rule-based transaction categorisation, eliminating errors caused by manual interpretation.
- Improved financial reporting reliability through consistent, audit-ready reconciliation records with full exception visibility.
Key Learnings & Achievement
- A reusable reconciliation framework with configurable MT940 parsing, rule-based categorisation, ERP matching logic, and exception workflows enables faster replication across entities and banks — creating a proven, audit-ready model that builds client confidence and supports scalable automation adoption.
- Managing multi-bank MT940 variations requires strong parsing logic and accurate reference extraction, while a hybrid RPA–SQL–ERP approach significantly improves match accuracy and reliability across high-volume reconciliation processes.
- Structured exception reporting is essential for transparency and audit readiness, ensuring unmatched transactions are easily identified, reviewed, and resolved without disrupting financial operations.
- Automation standardises reconciliation practices across the organisation, improving data consistency, strengthening financial control, and accelerating end-to-end reconciliation timelines.
